Mariangela Cerasuolo, Stefania De Marco, Raffaele Nappo, Roberta Simeoli, Angelo Rega
{"title":"虚拟现实通过提高自闭症谱系障碍特征来改善诊断评估的潜力:系统综述","authors":"Mariangela Cerasuolo, Stefania De Marco, Raffaele Nappo, Roberta Simeoli, Angelo Rega","doi":"10.1007/s41252-024-00413-1","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><p>While studies examining the effectiveness of virtual reality (VR) systems in autism spectrum disorder (ASD) intervention have seen significant growth, research on their application as tools to improve assessment and diagnosis remains limited. This systematic review explores the potential of VR systems in speeding-up and enhancing the assessment process for ASD.</p><h3>Methods</h3><p>We conducted a systematic search of peer-reviewed research to identify studies that compared characteristics of autistic and neurotypical participants performing tasks in virtual environments. Pubmed and IEE Xplore databases were searched and screened using predetermined keywords and inclusion criteria related to ASD and virtual reality, resulting in the inclusion of 20 studies.</p><h3>Results</h3><p>Studies reviewed revealed that VR technologies may serve as a booster of ASD “traits” that might otherwise go unnoticed when using traditional tools. Specifically, results indicated that ASD individuals exhibited distinct behavioral nuances compared to typically developing participants across four main domains: communication and social interaction skills, cognitive functioning and neurological pattern, sensory and physiological processing, and motor behavior and body movements. Also, recent studies analyzed here underscored the potential of integrating machine learning with VR technologies to enhance accuracy in identifying ASD based on motor behavior, eye gaze, and electrodermal activity.</p><h3>Conclusions</h3><p>The integration of VR technologies can complement traditional tools in ASD diagnosis, providing more objective and reliable assessment within a controlled, ecological, and motivating virtual environment. In addition, the reviewed literature suggests machine learning models combined with VR technologies may support phenotypic diagnosis, offering a more refined classification of ASD subgroups within immersive virtual contexts.</p></div>","PeriodicalId":36163,"journal":{"name":"Advances in Neurodevelopmental Disorders","volume":"9 1","pages":"1 - 22"},"PeriodicalIF":1.3000,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Potential of Virtual Reality to Improve Diagnostic Assessment by Boosting Autism Spectrum Disorder Traits: A Systematic Review\",\"authors\":\"Mariangela Cerasuolo, Stefania De Marco, Raffaele Nappo, Roberta Simeoli, Angelo Rega\",\"doi\":\"10.1007/s41252-024-00413-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><p>While studies examining the effectiveness of virtual reality (VR) systems in autism spectrum disorder (ASD) intervention have seen significant growth, research on their application as tools to improve assessment and diagnosis remains limited. This systematic review explores the potential of VR systems in speeding-up and enhancing the assessment process for ASD.</p><h3>Methods</h3><p>We conducted a systematic search of peer-reviewed research to identify studies that compared characteristics of autistic and neurotypical participants performing tasks in virtual environments. Pubmed and IEE Xplore databases were searched and screened using predetermined keywords and inclusion criteria related to ASD and virtual reality, resulting in the inclusion of 20 studies.</p><h3>Results</h3><p>Studies reviewed revealed that VR technologies may serve as a booster of ASD “traits” that might otherwise go unnoticed when using traditional tools. Specifically, results indicated that ASD individuals exhibited distinct behavioral nuances compared to typically developing participants across four main domains: communication and social interaction skills, cognitive functioning and neurological pattern, sensory and physiological processing, and motor behavior and body movements. Also, recent studies analyzed here underscored the potential of integrating machine learning with VR technologies to enhance accuracy in identifying ASD based on motor behavior, eye gaze, and electrodermal activity.</p><h3>Conclusions</h3><p>The integration of VR technologies can complement traditional tools in ASD diagnosis, providing more objective and reliable assessment within a controlled, ecological, and motivating virtual environment. In addition, the reviewed literature suggests machine learning models combined with VR technologies may support phenotypic diagnosis, offering a more refined classification of ASD subgroups within immersive virtual contexts.</p></div>\",\"PeriodicalId\":36163,\"journal\":{\"name\":\"Advances in Neurodevelopmental Disorders\",\"volume\":\"9 1\",\"pages\":\"1 - 22\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2024-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Neurodevelopmental Disorders\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s41252-024-00413-1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"EDUCATION, SPECIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Neurodevelopmental Disorders","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s41252-024-00413-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"EDUCATION, SPECIAL","Score":null,"Total":0}
引用次数: 0
摘要
目的尽管对虚拟现实(VR)系统在自闭症谱系障碍(ASD)干预中的有效性进行的研究有了显著增长,但将其作为改进评估和诊断工具的研究仍然有限。本系统性综述探讨了虚拟现实系统在加速和增强自闭症评估过程中的潜力。方法我们对同行评审的研究进行了系统性检索,以确定对自闭症患者和神经畸形患者在虚拟环境中执行任务的特征进行比较的研究。我们使用预先确定的关键词和与 ASD 和虚拟现实相关的纳入标准对 Pubmed 和 IEE Xplore 数据库进行了搜索和筛选,最终纳入了 20 项研究。ResultsStudies reviewed reveals that VR technologies may serve as a booster of ASD "traits" that might else go noticed when using traditional tools.具体而言,研究结果表明,与发育正常的参与者相比,ASD 患者在以下四个主要领域表现出明显的行为细微差别:沟通和社会交往技能、认知功能和神经模式、感官和生理处理以及运动行为和肢体动作。此外,本文分析的近期研究还强调了将机器学习与 VR 技术相结合的潜力,以提高根据运动行为、眼睛注视和皮电活动识别 ASD 的准确性。结论VR 技术的整合可以补充 ASD 诊断的传统工具,在可控、生态和激励性的虚拟环境中提供更客观、更可靠的评估。此外,综述文献表明,机器学习模型与 VR 技术相结合可支持表型诊断,在身临其境的虚拟环境中对 ASD 亚群进行更精细的分类。
The Potential of Virtual Reality to Improve Diagnostic Assessment by Boosting Autism Spectrum Disorder Traits: A Systematic Review
Objectives
While studies examining the effectiveness of virtual reality (VR) systems in autism spectrum disorder (ASD) intervention have seen significant growth, research on their application as tools to improve assessment and diagnosis remains limited. This systematic review explores the potential of VR systems in speeding-up and enhancing the assessment process for ASD.
Methods
We conducted a systematic search of peer-reviewed research to identify studies that compared characteristics of autistic and neurotypical participants performing tasks in virtual environments. Pubmed and IEE Xplore databases were searched and screened using predetermined keywords and inclusion criteria related to ASD and virtual reality, resulting in the inclusion of 20 studies.
Results
Studies reviewed revealed that VR technologies may serve as a booster of ASD “traits” that might otherwise go unnoticed when using traditional tools. Specifically, results indicated that ASD individuals exhibited distinct behavioral nuances compared to typically developing participants across four main domains: communication and social interaction skills, cognitive functioning and neurological pattern, sensory and physiological processing, and motor behavior and body movements. Also, recent studies analyzed here underscored the potential of integrating machine learning with VR technologies to enhance accuracy in identifying ASD based on motor behavior, eye gaze, and electrodermal activity.
Conclusions
The integration of VR technologies can complement traditional tools in ASD diagnosis, providing more objective and reliable assessment within a controlled, ecological, and motivating virtual environment. In addition, the reviewed literature suggests machine learning models combined with VR technologies may support phenotypic diagnosis, offering a more refined classification of ASD subgroups within immersive virtual contexts.
期刊介绍:
Advances in Neurodevelopmental Disorders publishes high-quality research in the broad area of neurodevelopmental disorders across the lifespan. Study participants may include individuals with:Intellectual and developmental disabilitiesGlobal developmental delayCommunication disordersLanguage disordersSpeech sound disordersChildhood-onset fluency disorders (e.g., stuttering)Social (e.g., pragmatic) communication disordersUnspecified communication disordersAutism spectrum disorder (ASD)Attention-deficit/hyperactivity disorder (ADHD), specified and unspecifiedSpecific learning disordersMotor disordersDevelopmental coordination disordersStereotypic movement disorderTic disorders, specified and unspecifiedOther neurodevelopmental disorders, specified and unspecifiedPapers may also include studies of participants with neurodegenerative disorders that lead to a decline in intellectual functioning, including Alzheimer’s disease, amyotrophic lateral sclerosis, Creutzfeldt-Jakob disease, vascular dementia, Lewy body dementia, frontotemporal dementia, corticobasal degeneration, Huntington’s disease, and progressive supranuclear palsy. The journal includes empirical, theoretical and review papers on a large variety of issues, populations, and domains, including but not limited to: diagnosis; incidence and prevalence; and educational, pharmacological, behavioral and cognitive behavioral, mindfulness, and psychosocial interventions across the life span. Animal models of basic research that inform the understanding and treatment of neurodevelopmental disorders are also welcomed. The journal is multidisciplinary and multi-theoretical, and encourages research from multiple specialties in the social sciences using quantitative and mixed-method research methodologies.